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Abstract
The aims of this research are: (1) to analyze the growth classification of economic sectors in the Wajo Regency 2011-2015; (2) to analyze the basic sector of the economy in the Wajo Regency 2011-2015; (3) to analyze the share and shifts in the economy sector Wajo Regency 2011-2015. This study uses secondary data obtained from BPS-Statistics South Sulawesi Province, BPS-Statistics Wajo, and the Department of Planning and Regional Development Wajo. Data were analyzed using Klassen Typology, Location Quotient, and Shift-Share analysis. The results of this research show that: (1) Sector classified as a developed sectors in the Wajo Regency is The of Agriculture, Forestry and Fisheries, and sector mining and excavation. (2) sectors is a basic sector of Wajo Regency is the sector of Agriculture, Forestry and Fisheries, sector mining and excavation, sector Procurement Electricity and Gas, the sector of Wholesale and Retail, Car Repair, and Motorcycles, (3) The structure of the Wajo Regency 2011-2015 start forward to slide in the economic sector from primer sector to secondary sector (4). The sectors that have competitive advantages (D) in Wajo are sectors of Agriculture, Forestry and Fisheries, sector Procurement Electricity and Gas, construction sector, sectors Transportation and Warehousing, sector Provision of Accommodation and Food Drink, the Financial Services sector and the insurance sector, Real Estate sector, Service sector Corporate sector Public Administration, Defense, and Social Security Mandatory, and sector service of education.
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References
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References
Billings, S. B., & Johnson, E. B. (2012). The location quotient as an estimator of industrial concentration. Regional Science and Urban Economics, 42(4), 642–647. https://doi.org/https://doi.org/10.1016/j.regsciurbeco.2012.03.003
Grossi, L., & Mussini, M. (2018). A spatial shift-share decomposition of electricity consumption changes across Italian regions. Energy Policy, 113, 278–293. https://doi.org/https://doi.org/10.1016/j.enpol.2017.10.043
Grunschel, C., Patrzek, J., & Fries, S. (2013). Exploring different types of academic delayers: A latent profile analysis. Learning and Individual Differences, 23, 225–233. https://doi.org/https://doi.org/10.1016/j.lindif.2012.09.014
Khusaini, M. (2015). A Shift-share Analysis on Regional Competitiveness - A Case of Banyuwangi District, East Java, Indonesia. Procedia - Social and Behavioral Sciences, 211, 738–744. https://doi.org/https://doi.org/10.1016/j.sbspro.2015.11.097
Lin, G., Jiang, D., Fu, J., Wang, D., & Li, X. (2019). A spatial shift-share decomposition of energy consumption changes in China. Energy Policy, 135, 111034. https://doi.org/https://doi.org/10.1016/j.enpol.2019.111034
Mogila, Z., Ciolek, D., Kwiatkowski, J. M., & Zaucha, J. (2021). The Baltic blue growth – A country-level shift-share analysis. Marine Policy, 134, 104799. https://doi.org/https://doi.org/10.1016/j.marpol.2021.104799
Park, J., & Ahn, Y. (2012). Strategic environmental management of Korean construction industry in the context of typology models. Journal of Cleaner Production, 23(1), 158–166. https://doi.org/https://doi.org/10.1016/j.jclepro.2011.10.032
Weschke, J., Oostendorp, R., & Hardinghaus, M. (2022). Mode shift, motivational reasons, and impact on emissions of shared e-scooter usage. Transportation Research Part D: Transport and Environment, 112, 103468. https://doi.org/https://doi.org/10.1016/j.trd.2022.103468
Yang, E., & Smith, J. W. (2023). The spatial and temporal resilience of the tourism and outdoor recreation industries in the United States throughout the COVID-19 pandemic. Tourism Management, 95, 104661. https://doi.org/https://doi.org/10.1016/j.tourman.2022.104661